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Chengliang Wang; Xiaojiao Chen; Zhebing Hu; Sheng Jin; Xiaoqing Gu – Journal of Computer Assisted Learning, 2025
Background: ChatGPT, as a cutting-edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated content (AIGC) technology, highlighting the need…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Computer Uses in Education
Lisana, Lisana – Education and Information Technologies, 2023
Adopting technology by its intended users is one of the most important contributors to that technology's success. Therefore, the success of mobile learning (ML) depends on the students' acceptance of the method. Regarding this point, this quantitative research aims to identify factors that affect switching intention to adopt ML among university…
Descriptors: Handheld Devices, Telecommunications, Technology Integration, Intention
Al-Emran, Mostafa; Al-Nuaimi, Maryam N.; Arpaci, Ibrahim; Al-Sharafi, Mohammed A.; Anthony, Bokolo – Education and Information Technologies, 2023
The emergence of wearable technologies, including smartwatches, has received a considerable attention from scholars across several sectors. However, there is a scarcity of knowledge regarding the determinants affecting the adoption of these wearables in education. Therefore, this research aims to propose a theoretical research model through the…
Descriptors: Educational Technology, Technology Uses in Education, Student Behavior, Intention
Patil, Harshali; Undale, Swapnil – Education and Information Technologies, 2023
The COVID-19 pandemic has prompted the adoption of an e-Learning pedagogy. This forced teachers and students to shift to online learning and thus was compelled to adopt online educational technology. Educational institutes have been facing challenges like insufficient infrastructure and a shortage of quality teachers. Online learning can help to…
Descriptors: COVID-19, Pandemics, Educational Technology, Electronic Learning
Rusman; Rusman O. Setiasih; Nandi; Wawan Setiawardani; Eri Yusron – Pegem Journal of Education and Instruction, 2024
This study aims to identify factors that can influence students when using the learning management system (LMS) in learning educational pedagogy. The LMS that we mean in this study is Pedagogi.id Platform. The design model in the study uses the UTAUT model. Questionnaires with five UTAUT variables, namely performance expectancy, effort expectancy,…
Descriptors: Learning Management Systems, Technology Integration, Educational Technology, Expectation
Adrian Szilard Nagy; Johan Reineer Tumiwa; Fitty Valdi Arie; László Erdey – Cogent Education, 2024
Higher education has seen substantial changes with the growing integration of computer-based intelligence technologies into the learning process. Nevertheless, the acceptance of computer-based intelligence in advanced educational settings is still faced with various difficulties, including perceived dangers, implementation assumptions, and…
Descriptors: Technology Integration, Artificial Intelligence, Technology Uses in Education, Risk
Unal, Erhan; Uzun, Ahmet Murat – British Journal of Educational Technology, 2021
Educational social network sites have many uses in the field of education. The present paper aims to determine factors influencing students' behavioral intention to use a popular educational social network site, Edmodo. Using an extension of the technology acceptance model, we analyzed quantitative responses of 218 university students, registered…
Descriptors: College Students, Intention, Social Media, Technology Integration
Sajuddin Saifi; Shaista Tanveer; Mohd Arwab; Dori Lal; Nabila Mirza – Education and Information Technologies, 2025
The current study is an attempt to bring to light the influence of Open AI adoption among users regarding the Indian Higher Education system by incorporating the TCT and TTF models. A questionnaire was designed to collect the data from 571 participants associated with higher education in India. The developed model with Perceived usefulness,…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Higher Education
Md. Rabiul Awal; Md. Enamul Haque – Journal of Applied Research in Higher Education, 2025
Purpose: This paper aims to explore students' intention to use and actual use of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in the field of higher education in an emerging economic context like Bangladesh. Design/methodology/approach: The present study uses convenience sampling techniques to collect data from the…
Descriptors: Foreign Countries, College Students, Intention, Artificial Intelligence
Jerri Alejandro López-Sánchez; Juan Camilo Patiño-Vanegas; Alejandro Valencia-Arias; Jackeline Valencia – Cogent Education, 2023
Information and communication technologies (ICTs) adopted in higher education are an impactful topic for the actors directly involved. For this reason, the use and adoption of ICTs aimed at university student learning was examined through a systematic review using PRISMA methodology; this review included 27 articles that met the inclusion…
Descriptors: Educational Technology, Technology Uses in Education, College Students, Technology Integration
Vishnu Lal; Vishvajit Kumbhar; G. Varaprasad – Knowledge Management & E-Learning, 2024
The study aims to improve the existing unified theory of acceptance and use of technology (UTAUT) framework to understand the adoption of e-learning platforms in developing countries and to understand the relevance of the quality of study life among students. The constructs for the UTAUT model were chosen based on the e-learning study context and…
Descriptors: Foreign Countries, Educational Technology, Electronic Learning, College Students
Joanna Pyrkosz-Pacyna; Marcin Zwierzdzynski; Jowita Guja; Maria Lis; Dominika Bulska – Educational Technology & Society, 2024
In this article, we present the results of research conducted to investigate the perception of VR educational materials for space technology courses being developed at a technological university in Europe. Our aim was to identify potential barriers faced by men and women when entering and continuing this form of education. As both VR and space…
Descriptors: Space Sciences, Computer Simulation, Educational Technology, Barriers
Anamika Chandra; Sarthak Sengupta; Anurika Vaish – Education and Information Technologies, 2025
E-learning systems have strengthened the learning process among students by providing online learning opportunities to them. With the diminishing difference between the academic world and the job markets, students must get the full benefits of e-learning platforms. The disparity in online learning opportunities due to a lack of resources has…
Descriptors: College Students, Intention, Electronic Learning, Student Behavior
Hanadi Aldreabi; Nisreen Kareem Salama Dahdoul; Mohammad Alhur; Nidal Alzboun; Najeh Rajeh Alsalhi – Electronic Journal of e-Learning, 2025
The examination of the impact of Generative AI (GenAI) on higher education, especially from the viewpoint of students, is gaining significance. Although prior research has underscored GenAI's potential advantages in higher education, there exists a discernible research gap concerning the determinants that affect its adoption. In the present study,…
Descriptors: Student Behavior, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Katarína Žáková; Diana Urbano; Ricardo Cruz-Correia; José Luis Guzmán; Jakub Matišák – Education and Information Technologies, 2025
Understanding how students interact with AI bots is a first step towards integrating them into instructional design. In this report, the results of a survey conducted in three European higher education institutions, and in the context of four different areas are presented. Among other things, they reveal for what purposes students use ChatGPT,…
Descriptors: Student Attitudes, Teacher Attitudes, Artificial Intelligence, Natural Language Processing